def formulate_expectation(self, word):
now = utilities.milliseconds(datetime.datetime.now())
activation = self.activation(word.times)
retrieval_prob = self.retrieval_probability(activation, CogModule.THRESHOLD, CogModule.NOISE)
retrieval_latency = self.retrieval_latency(CogModule.LATENCY, activation)
self.expectation = self.get_expectation_name(retrieval_prob)
status = str(retrieval_prob) + ': '
emotion = None
if self.expectation == 'positive':
status += 'Expecting right answer.'
emotion = CogModule.EXPECT_POS[0]
elif self.expectation == 'none':
status += 'Expecting nothing.'
elif self.expectation == 'negative':
status += 'Expecting wrong answer'
emotion = CogModule.EXPECT_NEG[0]
else:
print 'Wrong expectation value', self.expectation
self.logger.log(' Formulate expectation: prob={0:.2f}% latency={1:.2f}s : ({2},{3})'.format(retrieval_prob, retrieval_latency, self.expectation, emotion))
return (status, utilities.emotion_by_name(emotion))
def update_emo_status(self, data):
''' Gets a string of emotion values received from wasabi
and updates the internal emotion dictionary
1. Try: Always show dominating emotion
'''
# Update emotion status:
current = self.extract(data)
for emo in self.emo_status.keys():
if emo in current.keys():
self.emo_status[emo] = current[emo]
else:
self.emo_status[emo] = 0
# Get dominating emotion:
primary_emo = self.get_primary_emotion()
# Check for change:
if (not self.dominating_emo or (primary_emo and self.dominating_emo
and primary_emo.name != self.dominating_emo.name)):
#self.logger.log(' Dominating emotion changed to {}'.format(primary_emo))
self.dominating_emo = primary_emo
emotion = utilities.emotion_by_name(primary_emo.name)
# Send to MARC:
if self.marc:
if emotion.FREQUENCE <= self.count:
self.count = 0
self.marc.show(emotion)
else:
self.count += 1
def check(self, correct, expectation):
''' Task evaluation according to the emotional reaction.
Sends an emotional input to wasabi and text back to the agent
correct: correctness of the given answer: true / false
expecation: of the answer before answer was given:
negative / none / positive
'''
emotion = 'None'
impulse = 0
reactions = {'negative': {1: EmoModule.REACT_NEG_RIGHT,
0: EmoModule.REACT_NEG_WRONG,
2: EmoModule.REACT_NEG_NONE},
'none': {1: EmoModule.REACT_NONE_RIGHT,
0: EmoModule.REACT_NONE_WRONG,
2: EmoModule.REACT_NONE_NONE},
'positive': {1:EmoModule.REACT_POS_RIGHT,
0:EmoModule.REACT_POS_WRONG,
2:EmoModule.REACT_POS_NONE}}
surprise, emotion, impulse = reactions[expectation][correct]
self.logger.log(' Reaction: surprise:{}, emotion={}, impulse={}'.format(surprise, emotion, impulse))
if surprise:
self.trigger(Surprise())
if self.use_wasabi:
if emotion != 'None':
self.trigger(utilities.emotion_by_name(emotion))
if impulse != 0:
print 'IMPULSE IS NEG', impulse
self.impulse(impulse)
else:
self.show_static_emotion(utilities.emotion_by_name(emotion, impulse))
# TODO(How to wait here until first wasabi message is received?)
return self.get_primary_emotion()
def get_primary_emotion(self):
''' Get dominating emotion:
'''
# TODO(wait here for next received message)
if self.expressing:
primary_emo = ''
highest_imp = 0
for emotion in self.emo_status.keys():
if math.fabs(self.emo_status[emotion]) >= math.fabs(highest_imp):
primary_emo = emotion
highest_imp = self.emo_status[emotion]
if highest_imp == 0:
primary_emotion = 'concentrated'
return utilities.emotion_by_name(primary_emo, impulse = highest_imp)
else:
return self.static_emotion
def resolve_expectation(self, correct):
''' Cognitive reaction to correctness and times of a given word.
'''
reaction = 'none'
if self.expectation == 'negative':
if correct == 1:
reaction = CogModule.EXPECT_NEG[2]
elif correct == 0 or correct == 2:
reaction = CogModule.EXPECT_NEG[1]
else:
print 'WRONG CORRECT VALUE', correct
elif self.expectation == 'positive':
if correct == 1:
reaction = CogModule.EXPECT_POS[1]
elif correct == 0 or correct == 2:
reaction = CogModule.EXPECT_POS[2]
else:
print 'WRONG CORRECT VALUE', correct
str_answer = ['false', 'correct', 'notgiven'][correct]
self.logger.log(' Reaction to expectation={} and answer={}: {}'.format(self.expectation, correct, reaction))
return utilities.emotion_by_name(reaction)
